Podcli MCP Server

AI-powered podcast clip generator for TikTok/YouTube Shorts. Transcribe, find viral moments, export vertical clips with burned captions.

Local serverstdioPython

What is the Podcli MCP server?

AI-powered podcast clip generator for TikTok/YouTube Shorts. Transcribe, find viral moments, export vertical clips with burned captions. Exposed over MCP by the podcli mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.

What it actually does

Turn a long episode into short clips with face tracking and burned-in captions. Drive it from the CLI, a web studio, or your coding agent.

  • Runs locally. Transcription and rendering happen on your machine by default, so episodes stay there. Only the optional cloud engine (AssemblyAI) and publishing to YouTube send anything out
  • Free and open source under AGPL-3.0. Exports are unlimited, full quality, and watermark-free
  • Agent-native. 26 MCP tools let Claude Code or Codex drive the whole flow, transcription through publishing
  • A knowledge base keeps titles, captions, and descriptions in your show's voice, and stops the engine from resuggesting moments you already published
  • DaVinci Resolve handoff. Export any clip as FCPXML when you want to finish the edit yourself

Its toolset

Everything the assistant can do here goes through one of these:

  • Multi — segment cuts that drop filler, long pauses, and tangents
  • Loudness — normalized audio and hardware encoding on VideoToolbox, NVENC, and VAAPI, with a CPU fallback
  • Agent — native. 26 MCP tools let Claude Code or Codex drive the whole flow, transcription through publishing
  • Guide — What's in it

Adding it to your client

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.

When to reach for it

Among the developer tooling options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Podcli's toolset — Multi, Loudness, Agent and 1 more — is a fair guide to whether it matches your workflow. It is maintained by nmbrthirteen; worth a glance at recent repository activity before you build anything load-bearing on it.

This entry was verified against Podcli's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.

Caveats

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the podcli mcp server does with a few real requests.

Available tools

ToolWhat it does
Multisegment cuts that drop filler, long pauses, and tangents
Loudnessnormalized audio and hardware encoding on VideoToolbox, NVENC, and VAAPI, with a CPU fallback
Agentnative. 26 MCP tools let Claude Code or Codex drive the whole flow, transcription through publishing.
GuideWhat's in it

Example prompts to try

  • Use Podcli to Multi.
  • Use Podcli to Loudness.
  • Use Podcli to Agent.

Frequently asked questions

It connects Podcli to MCP-compatible AI assistants such as Claude and Cursor, exposing 4 tools (Multi, Loudness, Agent, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Podcli directly.